September 2024
Beginner to intermediate
364 pages
8h 27m
Korean
Content preview from 머신러닝 인터뷰 실무 가이드
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141
CHAPTER 03
기술 인터뷰: 머신러닝 알고리즘
더 멀리
NLP
는 (그림
3
-
11
에 설명한 바와 같이 ) 최근 몇 년 동안 잘 알려진 대규모 언어 모델
(
LLM
)들이 많이 출시되면서 빠르게 성장하고 있습니다. 이 분야에 관심이 있다면 이러한 모
델과 기술에 대해 더 배우기를 권합니다. 저는 회사에서
Word2vec
42
과
GloVe
43
를 살펴본
기억이 있는데, 지금은
NLP
애플리케이션을 개발하는 수많은 방법이 존재합니다.
BERT
와
같은 모델뿐만 아니라
Word2vec
,
GloVe
같은 기초적인 방법도 널리 사용되고 있으며, 제
가 알고 지내는 채용 매니저들은 지금도 인터뷰에서 해당 기법들에 관해 물어보고 있습니다.
그러니 기초를 무시하면 안 됩니다!
LLM
의 진화
그림
3-11
대규모 언어 모델의 진화, 출처: 대규모 언어 모델을 위한 실무 가이드(
https
://
oreil
.
ly
/
eVJEK
)
42
‘
Word2vec
,’ 위키피디아,
2023
년
9
월
5
일 업데이트,
https
://
oreil
.
ly
/
JyqBW
.
43
제프리 페닝턴, 리처드 소처, 크리스토퍼
D
. 매닝, 『
GloVe
: 단어 표현을 위한 글로벌 벡터 』
Stanford
University
,
2014
년
8
월,
https
://
oreil
.
ly
/
LdCcH
.
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.